Many studies have been conducted in the field of bankruptcy prediction; But in most of them only financial ratios are used. However, in Iran, many non-financial factors affect bankruptcy. The main purpose of this study is to develop a mathematical model in which financial and non-financial indicators such as management and economics factors are used to predict bankruptcy. In this study, 44 variables that had the greatest impact on bankruptcy forecast were selected and with confirmatory factor analysis, a questionnaire was developed and sent to experts in the fields of management, accounting and economics to rank the impact of these variables. The statistical sample of the study includes 200 bankrupt and non-bankrupt companies listed in the period 2009-2018. After collecting the questionnaires using the OLS regression estimation method, the variables that had a factor load of less than 0.5 were eliminated and in the final model 9 main variables. The research model identified 95% of bankrupt companies and 93% of non-bankrupt companies with 95.4% confidence. Then, for verification, two hypotheses were developed and the model of this research was compared with two existing models. The ability to distinguish bankrupt companies from non-bankrupt ones by our proposed model was 6% more accurate than the Pourheidari et al. model, and 9.4% more accurate than Altman’s model.
Daily net cash flow analysis and forecasting : Transition from Microscopic to Macroscopic Stochastic Equations(مقاله علمی وزارت علوم)
The purpose of this study is a new understanding behaviour and net cash flow forecasting. The data of this research contains the daily trial balance for one year, which has been received from 48 bank branches. For this purpose, the optimal model out of 4 models; Geometric Brownie, Arithmetic Brownie, Vasicek and Modified Square Root at three levels of microscopic, mesoscopic and macroscopic have been investigated and the Geometric Brownie model has been approved as the optimal model in microscopic level . The results show that Geometric Brownian Motion model can simulate the net cash flow highly accurate in accordance with the criteria of mean absolute percentage error. also forecasting net cash flow for each under study time series has been done in various forecasting horizons involved 7, 14, 21, 30, 60, 90 and 180 day time period accordance with the criteria of mean absolute percentage error. Also The other results obtained from this study is that according to 8 different prediction accuracy criteria, By increasing the forecast hori-zon, ability of the GBM model in simulation and forecasting the net cash flow de-creases.
Investigating the Impact of National Currency Value Shocks on the Inflation Structure and Unemployment of the New Keynesian Model Using a Dynamically Computable General Equilibrium Approach(مقاله علمی وزارت علوم)
The direct effect of shocks is to create uncertainty in economic variables. These unpredictable fluctuations influence all economic decisions of the government and the private sector. Also, the formation of people's expectations causes these shocks to have dynamic effects on all economic variables. Inflation is a general, disproportionate, and self-inflicted rise in prices that is often irreversible. The purpose of this study is to investigate the structure of inflation and unemployment of the new Keynesian model with a dynamic general equilibrium approach. Also in this study, dynamic CGE models of long-term relationships related to the decisions of economic institutions such as households and investors were used. Data were analyzed using the proposed practical models. According to the results, inflation in the whole country increases with currency shock. The stronger the currency shock, the stronger the consequent increase in inflation. But unemployment is temporarily reduced by a currency shock.
Evaluation the profitability of dynamic investment projects by using ordered fuzzy numbers(مقاله علمی وزارت علوم)
The purpose of this paper is to provide a new approach to incorporating uncertainty into assessing the profitability of investment projects. In the real world, the capital budgeting problem is accompanied by uncertainty and risk associated dealing with imprecise data. The major contribution of this research is the development of a novel approach to evaluating the profitability of an investment project in uncertainty condition. At first, we presented a new discount method that can be used by investors when they wants to be able to make an investment decision. That is, we developed a new method to evaluate the profitability of investment projects by or-dered fuzzy net present value (OFNPV). In addition, ordered fuzzy numbers (OFN) are used to describe the dynamics of changes of the defined investment parameters in the assumed time horizon. By using ordered fuzzy numbers, we develop an effective tool for assessing the profitability of investment projects. This assessment tool not only enables decision-makers to decide under uncertainty conditions whether or not a given investment project should be carried out or rejected, but also facilitates selecting the most effective project, e.g. a project with the most expected probability of success.
Investigating the Effect of Institution's Financial Development on the Economic Growth in MENA Countries Using PSVAR and Markov Switching Models(مقاله علمی وزارت علوم)
The financial sector plays a central role in economic development and growth, and due to playing an intermediary role in allocating resources to all sectors of the economy, by reducing financing costs and encouraging savings and their efficient use, a major contribution. In the long-term economic growth of the government in oil-exporting countries, relying on oil revenues, it is possible to enter the financial markets extensively and make various changes in it. The main goal of policymakers from such changes is to stimulate economic growth. But studies in this area show that fiscal development does not necessarily lead to economic growth. However, in recent decades, the role of financial development in economic growth has been forgotten. Therefore, this study examines the impact of the development of financial institutions on economic growth. The statistical population of the present study consists of MENA member countries in the period 1980 to 2019. In order to conduct this research, due to the nonlinear relationship between the research variables, the PSTR model and Markov switching time series pattern have been used. Financial depth, accessibility and efficiency are also variables in the development of financial institutions that have been considered in this study. The results indicate that all three components of the financial institutions development index have a significant effect on the economic growth variable.
Meta-analysis of auditor characteristics and profit quality (Considering auditor characteristics indicators)(مقاله علمی وزارت علوم)
The purpose of this study is to perform a meta-analysis of the relationship between auditor characteristics and profit quality. In order to integrate the results of different researches and identify the factors that modulate the relationships between auditor characteristics and profit quality, in this research we will use meta-analysis methodology which is one of the quantitative statistical methods. In order to implement the meta-analysis method, they were identified and collected from the websites of foreign journals (articles published in the period 2005 to 2020) and the Internet site of domestic scientific research journals (articles published during the years 2006 to 2021) as a statistical population of the research. Systematic removal has finally analyzed 50 studies; The results of studies conducted in the period and around this relationship indicate that most of these studies are heterogeneous. In order to identify the cause of this heterogeneity, by dividing the research based on different criteria for measuring profit quality and auditor characteristics and calculating intra-group chi-square statistics, we found that these different measurement criteria used in research are one of the factors of contradiction in the results. There have been researches. In the following study, it was observed that there is no significant relationship between auditor characteristics with profit smoothing and timely profit and also between non-audit services provided by the auditor and profit quality, while in contrast, there is no significant relationship between auditor characteristics and quality of accruals; Profit stability; There is the ability to predict profit and conservatism.
A Feasibility Study of Dissecting Stock Price Momentum Using Financial Statement Analysis(مقاله علمی وزارت علوم)
This paper sought to address the feasibility of dissecting stock price momentum in the firms listed in Tehran Stock Exchange using financial statement analysis (FSA). Different variables including those related to profitability, financial leverage and liquidity, and operating efficiency were used in this analysis. The study sample consisted of 130 firms listed in Tehran Stock Exchange over the period 2008-2019. The results showed that fundamental factors affected stock price momentum for one year in the winning portfolio and for two years in the losing one; after this period, financial information did not have a significant effect on stock price momentum. Therefore, stock price momentum performance is a function of the conformance of the past price performance to fundamentals. The results from investment strategies based on the past price performance-fundamentals conformance indicated that fundamentals cause a significant difference in stock excess returns in winning and losing portfolios.
Investigating the Market Efficiency in Tehran Stock Exchange through Artificial Intelligence(مقاله علمی وزارت علوم)
This study was an attempt to evaluate the progress of capital market efficiency in Iran. Optimal resource allocation and micro and macro investments play a key role in the capital market. The capital market's main task is to circulate capital and allocate resources efficiently and optimally. The main task of this market is to flow capital and allocate resources efficiently and optimally. Is there a regular pattern for determining the stock price? Market efficiency gains significance as it is important to know what factor or factors are effective in determining the price of the stock in the stock market or whether there is a regular pattern for determining the price of a stock. Thus, this study examined the efficiency of the capital market in Iran. In this regard, the researchers used the daily data of the total index of the Tehran Stock Exchange for 2008-2017. Artificial neural network and time series training tests were used to perform the test. The test results showed weak efficiency in the Tehran Stock Exchange and this inefficiency did not change significantly compared to the first period. In other words, in the Tehran Stock Market, one can predict returns using artificial intelligence.
Study of ranking factors affecting the implementation of timely management of goods and equipment and its evaluation criteria in the power distribution company of the whole country using fuzzy AHP and fuzzy DEMATEL(مقاله علمی وزارت علوم)
The aim of this study was to investigate the ranking of effective factors on how to implement timely management of goods and equipment and its evaluation criteria in the power distribution company of the whole country using Analytic Hierarchy (AHP). Five dimensions (production technical factors, managerial level management factors, factors related to IT processes and infrastructure, factors related to processes and factors related to training and manpower) were determined and the research hierarchical tree was drawn. Based on the opinions of experts in this tree, five Next, on how to implement timely management of goods and equipment in time and its criteria interact with each other. To determine their weight, the combined approach of fuzzy AHP and fuzzy DEMATEL was used. The influential and expressive dimensions of each other are the cause, and the dimensions of the factors related to IT processes and infrastructures are part of the influential or expressive dimensions of other effects.
Investigating the role of development banks in fixed investment formation in Iran(مقاله علمی وزارت علوم)
This paper examines the role of development banks in the fixed investment formation and economic growth of the country with emphasis on the facilities granted by development banks. To do this, quarterly data of the country's development banks in the period 2006-2020 and experimental tests related to the causal relationship of variables and estimating the long-run relationship between variables were used with the Granger causality test and vector autoregression method (var). The results show that the development sector facilities and total banking network facilities (except for development sector facilities) have had positive and significant effects on fixed investment formation and other banking network payment facilities except the development sector and liquidity volume have had no significant effcets. Regarding the relationship between the liquidity and total paid facilities of the banking system, with the variable of fixed investment formation, the results show that all paid facilities have had positive and significant effects and liquidity has insignificant effects on fixed investment formation. According to the results of the long-run relationship, the development sector facilities and the volume of liquidity, in the long run, have had a significant relationship with fixed investment formaton in the Iranian economy. According to the results of the short-run relationship, development sector facilities have had positive and significant impacts on fixed investment formation and investment in the economy. Therefore, it can be concluded that the development sector facilities in both the short-term and long-term have been able to have a positive and significant effect on fixed investment formation
Investor expectations future economic processes are among the crucial factors affecting their decisions. The expectations seem to play a specific role since they are unsupervised variables capable of forming observable economic phenomena. Psychological factors influence investor expectations and corporate market value. Investor sentiments was modelled with an emphasis on psychological factors based on the Grounded Theory (GT). This applied and mixed-methods at its first and second stages. The statistical population comprised 13 experts, senior managers of investment companies, and university professors. The participants were selected through purposive and snowball sampling and the process was continued until theoretical saturation. The data were collected via semi-structured interviews coded via Atlas.ta.8 software. The research data were analysed using an open coding method. The results of the research were presented in 46 categories and 6 key dimensions.
An Optimization Model for Designing a Supply Chain Network with a Value-Based Management Approach(مقاله علمی وزارت علوم)
Traditional approaches applied in supply chain management consider only the physical logistic operations and ignore the financial aspects of the chain. In this study, a mathematical model has been developed to address the supply chain network design problem with a value-based management approach. This model integrates both operations and financial aspects to maximize the value created and measured by shareholder value analysis (SVA) as an objective function. The results attributed to the developed model and the basic model are compared. The results indicate that creating more value for the company and its shareholders is achievable with appropriate financial decisions. To validate and show the applicability of the proposed model, it was solved by GAMS software with data provided by literature. Finally, sensitivity analyses on financial parameters were performed to evaluate the results. The results clearly reveal the improvement of using the new approach and convince managers to take advantage of the proposed approach.
Providing a model of earning transparency with emphasis on the criteria of the govermance system and performance: an artificial intelligence approach(مقاله علمی وزارت علوم)
The present study is aimed to present a model of earnings transparency with an artificial intelligence approach in companies listed on the Tehran Stock Exchange (TSE). For this purpose, the data of 167 companies during the years 2011 to 2018 were used to test the research hypotheses. Variable selection test performed using Lasso's artificial intelligence algorithm showed that among the criteria of the audit committee's independence management system, the non-executive managers ratio, gender diversity and among the performance criteria, the ratio of cash holding in the company, operating profit margin and accounts receivable ratio had the highest effect to explain the earnings transparency of companies and also to predict the earnings transparency of the companies in the next year, the LARS algorithm method was used. The results of prediction showed the high power of Lars artificial intelligence algorithm to predict the earnings transparency of the companies listed on Tse. Keywords: Earnings Transparency, Corporate governance and performance criteria, Artificial Intelligence Approach
Analyzing the performance of DEA models for bankruptcy prediction in the energy sector: with emphasis on Dynamic DEA approach(مقاله علمی وزارت علوم)
Predicting bankruptcy risk is one of the most critical issues in corporate financial decision-making. Investors always try to predict the bankruptcy of a firm to reduce the risk of losing their assets, so they are looking for ways by which they can predict the risk of bankruptcy. We predict the position of companies active in the oil and gas industry based on their financial health in the 2020 ranking of S&P global up to three years before 2020. This study uses three data envelopment analysis models (CCR, BCC, and DDEA) and the traditional Altman model for forecasting. We have shown that dynamic data envelopment analysis is a powerful tool for predicting bankruptcy risk.
Presenting and explaining the model of the role of behavioral characteristics and financial literacy of real investors on their financial management components in the Iranian capital market(مقاله علمی وزارت علوم)
The purpose of this study is to present and explain the paradigm model of the role of behavioral characteristics and financial literacy of real investors on the components of their financial management behavior in the Iranian capital market. For this purpose, a 77-item questionnaire derived from qualitative studies using grounded theory method was used. The chi-square value of the model is equal to 3946.370, the degree of freedom of the model is equal to 2174, the result of which is equal to 1.815, and the fit indices of the original model are all in an acceptable and appropriate level. Behavioral characteristics and financial literacy can predict financial management behavior and help real investors analyze stock market trends before making a decision, which leads to investment profitability, financial security and capital satisfaction.
Investigating the effects of time variables of gold, crude oil and foreign exchange markets on herding behavior in Tehran Stock Foreign exchange(مقاله علمی وزارت علوم)
Due to overlap between stock markets and financial markets, this study was an attempt to examine the herding behavior in the Iranian stock market and the crude oil, foreign exchange and gold markets. For this purpose, in this research, monthly data between 2011 and 2020 for Tehran Stock Foreign exchange were used. The results of the study based on two criteria explaining herding behavior indicate the existence of herding behavior of the stock market and crude oil, gold and foreign exchange markets. The results also show that it has had different ef-fects on herding behavior in different periods. This issue has also been different in increasing and decreasing market periods. Therefore, gold is introduced as an important asset that influences herding behavior. Also, during the decreasing period of the stock market, herding behavior is not affected by the exchange and crude oil market, and in this period, the behavior of investors and investment risks in the stock market can be predicted without considering the exchange and crude oil market.
Presenting the smart pattern of credit risk of the real banks’ customers using machine learning algorithm(مقاله علمی وزارت علوم)
In the past, deciding over granting loans to bank customers in Iran would be made traditionally and based on personal judgments over the risk of repayment. However, increase in demands on banking facilities by economic enterprises and families on the one side, and increased as well as extended commercial competitions among banks and financial and credit institutions in the country for reduction of facility repayment risk on the other side, have caused application of novel methods such as some statistical ones in this context. Now to predict the risk of negligence in banking facility repayment and classification of the candidates, bankers use their customers’ credit ranking. Time efficiency, cost effectiveness, avoidance from personal judgments, and further accuracy in examining the candidates who apply for various funds are of its salient merits of this new combined method. Various statistical methods including biased analysis, logistic regression, non-parametric parallelism, and also some others such as neural networks have been employed for credit ranking. In this research, given the random forest metaheuristic algorithm-based smart pattern of real bank customers’ credit risk (case study: Bank Tejarat) was presented. According to the value of skewness, the data could be stated to have a normal distribution. Based on the observed results, the lowest mean was related to the variable of type of facility and its maximum value, to the amount of facility.
Providing an intelligent credit risk management system of the bank based on the macroeconomic indicators in the country's stock exchange banks(مقاله علمی وزارت علوم)
This study focuses on providing an intelligent credit risk management system of the bank in the presence of the macroeconomic indicators using a combined methodology of econometrics and artificial intelligence. In addition to the use of scientific documents and reports, the panel data related to the annual reports and datasets of stock exchange banks are analyzed by using the MATLAB programming environment. One of the most important results of the this paper is that the proposed approach has been based on the calculations made with the GARCH economic model in which the input values of the component "Inflation rate factor (A4)” have a weight of 0.943734 (equivalent to the membership function "High H"); the component "rate factor Bank deposit (B4)” has a weight of 0.959346 (equivalent to the "High H" membership function); the component “Unemployment rate factor (A3)” has a weight of 0.990343 (equivalent to the "High H" membership function); the component "Exchange Rate Factor (B2)" has a weight of 0.990413 (equivalent to the membership function "High H"); And the component "GDP growth rate factor (A1)” has a weight of 0.959256 (equivalent to the membership function of "high H"); This means that, 5.46 is within a range of 6, i.e. the target variable is exactly in the 91st position (the fifth level of the system output is excellent).
A Hybrid Entropy-TOPSIS Method to Investigate the Effect of Auditing Team Norms and Peer Personality Components on the Objectivity of Financial Auditors(مقاله علمی وزارت علوم)
Auditors' personality traits have a significant effect on the motivation of their financial behavior. In fact, the personal and personality traits of auditors that can be influenced by the environment play an important role in motivating individuals to engage in financially professional behaviors. Audit team norms are one of the factors in the audit firm environment that affect the auditor's behavior. In this study, the effect of auditing team norms and auditors' personality types on auditor objectivity was investigated. The Entropy technique is used to examine the importance of the norms of the audit team and the personality components of the peers, and based on the results and using the TOPSIS method, these factors affecting the objectivity of financial auditors are ranked. The statistical population of this study includes all professional auditors working in the auditing organization and private auditing institutions, members of the Iranian Society of Certified Public Accountants in 2020, including 242 members. The results showed that extroverted and responsible personality types have a positive and significant effect on auditors' objectivity. The results also showed that the norms of the audit team have a positive and significant effect on the objectivity of auditors.
Designing an Analytical Model for Assessing Supply Chain Re-silience to different Types of Risks: Case Study of Iran Petro-chemical Industries(مقاله علمی وزارت علوم)
The purpose of the study is to develop and test an analytical model for resilience assessment of supply chain risks against the risks of system and its individual tiers. In this regard a multi-method research approach is adopted as follows: By using data envelopment analysis (DEA) and fuzzy set theory, a fuzzy network DEA model has been proposed to assess risk in overall supply chains and their individual tiers. The proposed model is tested by surveying of 130 people as selective petrochemical companies in Iran. The survey results show a substantial variation in resilience ratings between the overall petrochemical supply chains and their individual tiers. The research findings indicate that system resilience is not necessarily indicative of the resilience of its individual tiers. On the other hand, high efficiency scores in supply chain tiers have limited influence on overall resilience of supply chain. The proposed analytical model enables the assessment of supply chain flexibility at different levels for a wide range of supply chain risks in upstream, downstream and downstream process-es.